Neural Representations for Sensory-Motor Control, III: Learning a Body-Centered Representation of 3-D Target Position

A neural model is described of how the brain may autonomously learn a body-centered representation of 3-D target position by combining information about retinal target position, eye position, and head position in real time. Such a body-centered spatial representation enables accurate movement commands to the limbs to be generated despite changes in the spatial relationships between the eyes, head, body, and limbs through time. The model learns a vector representation--otherwise known as a parcellated distributed representation--of target vergence with respect to the two eyes, and of the horizontal and vertical spherical angles of the target with respect to a cyclopean egocenter. Such a vergence-spherical representation has been reported in the caudal midbrain and medulla of the frog, as well as in psychophysical movement studies in humans. A head-centered vergence-spherical representation of foveated target position can be generated by two stages of opponent processing that combine corollary discharges of outflow movement signals to the two eyes. Sums and differences of opponent signals define angular and vergence coordinates, respectively. The head-centered representation interacts with a binocular visual representation of non-foveated target position to learn a visuomotor representation of both foveated and non-foveated target position that is capable of commanding yoked eye movementes. This head-centered vector representation also interacts with representations of neck movement commands to learn a body-centered estimate of target position that is capable of commanding coordinated arm movements. Learning occurs during head movements made while gaze remains fixed on a foveated target. An initial estimate is stored and a VOR-mediated gating signal prevents the stored estimate from being reset during a gaze-maintaining head movement. As the head moves, new estimates arc compared with the stored estimate to compute difference vectors which act as error signals that drive the learning process, as well as control the on-line merging of multimodal information.Air Force Office of Scientific Research (F49620-92-J-0499); National Science Foundation (IRI -87-16960, IRI-90-24877); Office of Naval Research (N00014-92-J-l309

The Effect of Scapular Fixation on Scapular and Humeral Head Movements during Glenohumeral Axial Distraction Mobilization

Background and Objectives: Glenohumeral axial distraction mobilization (GADM) is a usual mobilization technique for patients with shoulder dysfunctions. The effect of scapular fixation on the movement of the scapula and the humeral head during GADM is unknown. To analyze the caudal movement of the humeral head and the rotatory movement of the scapula when applying three different intensities of GADM force with or without scapular fixation. Materials and Methods: Fifteen healthy subjects (mean age 28 +/- 9 years; 73.3% male) participated in the study (twenty-eight upper limbs). Low-, medium- and high-force GADM in open-packed position were applied in scapular fixation and non-fixation conditions. The caudal movement of humeral head was evaluated by ultrasound measurements. The scapular rotatory movement was assessed with a universal goniometer. The magnitude of force applied during GADM and the region (glenohumeral joint, shoulder girdle, neck or nowhere) where subjects felt the effect of GADM mobilization were also recorded. Results: A greater caudal movement of the humeral head was observed in the non-scapular fixation condition at the three grades of GADM (p < 0.008). The rotatory movement of the scapula in the scapular fixation condition was practically insignificant (0.05-0.75 degrees). The high-force GADM rotated scapula 18.6 degrees in non-scapular fixation condition. Subjects reported a greater feeling of effect of the techniques in the glenohumeral joint with scapular fixation compared with non-scapular fixation. Conclusions: The caudal movement of the humeral head and the scapular movement were significantly greater in non-scapular fixation condition than in scapular fixation condition for the three magnitudes of GADM force

A Global optimization stochastic algorithm for head motion stabilization during quadruped robot locomotion

Visually-guided locomotion is important for autonomous robotics. However, there are several di culties, for instance, the robot locomotion induces head shaking that constraints stable image acquisition and the possibility to rely on that information to act accordingly. In this work, we propose a combined approach based on a controller architecture that is able to generate locomotion for a quadruped robot and a genetic algorithm to generate head movement stabilization. The movement controllers are biologically inspired in the concept of Central Pattern Generators (CPGs) that are modelled based on nonlinear dynamical systems, coupled Hopf oscillators. This approach allows to explicitly specify parameters such as ampli- tude, o set and frequency of movement and to smoothly modulate the generated oscillations according to changes in these parameters. Thus, in order to achieve the desired head movement, opposed to the one induced by locomotion, it is necessary to appropriately tune the CPG parameters. Since this is a non-linear and non-convex optimization problem, the tuning of CPG parameters is achieved by using a global optimization method. The genetic algorithm searches for the best set of parameters that generates the head movement in order to reduce the head shaking caused by locomotion. Optimization is done o ine according to the head movement induced by the locomotion when no stabilization procedure was performed. In order to evaluate the resulting head movement, a tness function based on the Euclidian norm is investigated. Moreover, a constraint handling technique based on tournament selection was im- plemented. Experimental results on a simulated AIBO robot demonstrate that the proposed approach generates head movement that reduces signi cantly the one induced by locomotion

Tracking human face features in thermal images for respiration monitoring

A method has been developed to track a region related to respiration process in thermal images. The respiration region of interest (ROI) consisted of the skin area around the tip of the nose. The method was then used as part of a non-contact respiration rate monitoring that determined the skin temperature changes caused by respiration. The ROI was located by the first determining the relevant salient features of the human face physiology. These features were the warmest and coldest facial points. The tracking method was tested on thermal video images containing no head movements, small random and regular head movements. The method proved valuable for tracking the ROI in all these head movement types. It was also possible to use this tracking method to monitor respiration rate involving a number of head movement types. Currently, more investigations are underway to improve the tracking method so that it can track the ROI in cases larger head movements

Forensic and clinical diagnosis in shaken baby syndrome , between child abuse and iatrogenic abuse

“Shaken baby syndrome” in child abuse cases is a challenge for pediatrician and forensic experts, often a diagnosis of exclusion, with overwhelming moral and legal implications. Diagnosis is based on: subdural bleeding, rupture of retinal vessels, traumatic diffuse axonal injury with diffuse brain encephalopathy in the absence of external traumatic injuries and anamnesis data of an accidentally head injury. Microscopic findings in diffuse axonal injuries were initially considered as a specific traumatic effect due to unrestricted movement and accelerated rotation of the head. Immunohistochemistry of beta amyloid protein precursor is gold standard method for identifying pathological diffuse axonal lesions, which is however non-specific in brain trauma. In the diagnosis of this syndrome pediatricians and forensic examiners must take into account the particularities of each case, avoiding scientific speculation, to intuit controversies and always be familiar with the differential diagnosis

Non-Instrumental Movement Inhibition (NIMI) differentially suppresses head and thigh movements during screenic engagement: dependence on interaction

BACKGROUND: Estimating engagement levels from postural micromovements has been summarized by some researchers as: increased proximity to the screen is a marker for engagement, while increased postural movement is a signal for disengagement or negative affect. However, these findings are inconclusive: the movement hypothesis challenges other findings of dyadic interaction in humans, and experiments on the positional hypothesis diverge from it. HYPOTHESES: (1) Under controlled conditions, adding a relevant visual stimulus to an auditory stimulus will preferentially result in Non-Instrumental Movement Inhibition (NIMI) of the head. (2) When instrumental movements are eliminated and computer-interaction rate is held constant, for two identically-structured stimuli, cognitive engagement (i.e., interest) will result in measurable NIMI of the body generally. METHODS: Twenty-seven healthy participants were seated in front of a computer monitor and speakers. Discrete 3-min stimuli were presented with interactions mediated via a handheld trackball without any keyboard, to minimize instrumental movements of the participant's body. Music videos and audio-only music were used to test hypothesis (1). Time-sensitive, highly interactive stimuli were used to test hypothesis (2). Subjective responses were assessed via visual analog scales. The computer users' movements were quantified using video motion tracking from the lateral aspect. Repeated measures ANOVAs with Tukey post hoc comparisons were performed. RESULTS: For two equivalently-engaging music videos, eliminating the visual content elicited significantly increased non-instrumental movements of the head (while also decreasing subjective engagement); a highly engaging user-selected piece of favorite music led to further increased non-instrumental movement. For two comparable reading tasks, the more engaging reading significantly inhibited (42%) movement of the head and thigh; however, when a highly engaging video game was compared to the boring reading, even though the reading task and the game had similar levels of interaction (trackball clicks), only thigh movement was significantly inhibited, not head movement. CONCLUSIONS: NIMI can be elicited by adding a relevant visual accompaniment to an audio-only stimulus or by making a stimulus cognitively engaging. However, these results presume that all other factors are held constant, because total movement rates can be affected by cognitive engagement, instrumental movements, visual requirements, and the time-sensitivity of the stimulus

The presence of head-raising and resumptive-stranding in Japanese relative clauses

Japanese relative clauses (RCs) show peculiar characteristics. For instance, while weak crossover effects reveal that relativization includes movement, the absence of island effects seems to demonstrate that relativization does not include movement. Ishii (1991) accounts for this peculiarity of Japanese RCs by his last-resort analysis; however, because of the Inclusiveness Condition (Chomsky 1995), this last-resort model is not tenable in the Minimalist Program (MP). Therefore, an improved characterization of Ishii’s last-resort analysis of relativization in Japanese is needed within the framework of the MP. In this paper, I claim that reconstruction/connectivity effects show that Japanese RCs include promotion/head-raising. I then propose that the amendment of Boeckx’s (2003) resumptive-stranding model, which includes promotion/head-raising of a relative head and pro-stranding, can offer an account of both the movement properties and non-movement properties of Japanese RCs. The proposed analysis conforms to Inclusiveness. Also, I claim that the unavailability of A-scrambling in Japanese RCs, which could be raised as an objection to the promotion/head-raising analysis, is due to the ban on Improper Movement (Müller — Sternefeld 1993; 1996)

Estimation of Confidence in the Dialogue based on Eye Gaze and Head Movement Information

In human-robot interaction, human mental states in dialogue have attracted attention to human-friendly robots that support educational use. Although estimating mental states using speech and visual information has been conducted, it is still challenging to estimate mental states more precisely in the educational scene. In this paper, we proposed a method to estimate human mental state based on participants’ eye gaze and head movement information. Estimated participants’ confidence levels in their answers to the miscellaneous knowledge question as a human mental state. The participants’ non-verbal information, such as eye gaze and head movements during dialog with a robot, were collected in our experiment using an eye-tracking device. Then we collect participants’ confidence levels and analyze the relationship between human mental state and non-verbal information. Furthermore, we also applied a machine learning technique to estimate participants’ confidence levels from extracted features of gaze and head movement information. As a result, the performance of a machine learning technique using gaze and head movements information achieved over 80 % accuracy in estimating confidence levels. Our research provides insight into developing a human-friendly robot considering human mental states in the dialogue